Electronic medical records in developing countries: A nine-year history and its future

Joaquin A. Blaya (on behalf of OpenMRS)Decision Systems Group, Brigham & Women’s HospitalPartners In Health

Outline

Multi-Drug Resistant Tuberculosis (MDR-TB) in Peru

• Palm project for health centers without Internet• e-Chasqui for health centers with Internet

HIV in Haiti

OpenMRS for the world

Commercial strategies in Chile

Problem Statement

Clinical data storage

Transportation - Mototaxi

Infrastructure

PIH-EMR in Peru

Secure web-based EMROperational since 2001 (Gates grant)Usable with low-speed dialup connectionsBilingual (Spanish/English)33,000 patients tracked7000+ patients treated for MDR-TBUsed in the Philippines (Tropical Disease Foundation)

SmearsCultures

DSTs

Drug regimensPharmacy

RegistrationformHistory/examPrevious RxPrevious DxContacts

Follow upChest X-ray

BiochemHematology

Clinical TB System: PIH-EMR

TeleMedMailWeb-based teleradiologyText

Email Server Specialist

Internet

Camara

Prediction of Medication Consumption

0 200000 400000 600000 800000 1000000 1200000 1400000 1600000

Amox/Clav

Capreomycin

Clarithromycin

Clofazamine

Cycloserine

Ethionamide

Kanamycin

Moxifloxacin

Pyridoxine

Ciprofloxin-eq

PAS

number of doses

PredictedUsageActualUsage

Predicted Peruvian 3-year drug usage to within 3%Annual cost of medications in 2003 was $2.7M

Palm project for community data collection

Community data collection (Palm)

To monitor MDR-TB patients a team collects lab results from over 126 health centers to enter them into PIH-EMR

Visit every health center

Collect 4400+ resultsevery month

Verify all results forcorrectness

System Development

JA Blaya, HSF Fraser AMIA Annu Symp 2006

Palm Pilot

PIH-EMR

Sync (PC)

Processing Section

Final Bacteriology Section

Processing & Verification

Lab Data

Patient Data

Randomized Controlled Trial

Delay times ErrorsIntervention

(days)

Control

(days)Pre-PDA 30.5* 30.8

Post-PDA 7.7*† 22.7†

* p < 0.001† p = 0.155

0

1

2

3

4

5

6

7

Total Errors

Perc

ent D

iscr

epan

cy

Intervention districts beforeControl districts afterIntervention districts after

*

*†

†

* p = 0.155† p < 0.001

* p < 0.001, † p < 0.001

Reduced workload by over 60% (p<0.001)

e-Chasqui to communicate lab results to clinicians

Problem Statement

• 10% of results took > 60 days to arrive at clinic*

− Possible loss of result

• Inability to track samples by clinical staff− Current status− History of tests performed

• 16% of patients waited >100 daysto start treatment

• Limited reporting and analysis capability

*Yagui et al. Int J Lung Dis 2006

Usage Statistics

99.2% of DSTS and 97.6% of culture results viewed online

e-Chasqui expanded from 12 to 212 HCs;from 2 to 4 labs

350+ users including clinicians, nurses, lab and research staff

System serves health centers that cover 4.1 million people~50% of all MDR-TB patients in Peru

0

1

2

3

4

5

6

Sep-05 Mar-06 Oct-06 Apr-07 Nov-07

Time

Even

ts p

er s

ite p

er r

esul

t

Page views per result per site

Culture Conversion TATRandomized Trial

ResultsIntervention HCs hadsignificantly lower times (p=0.04)

Control HCs 86 daysInterv. HCs 68 days

21% decrease (18 days) in intervention HCs

Results

1. Intervention HCs had a 91% less errors overall

2. System did not affect number of wrong name or result errors

Communication ErrorsRandomized Trial

Cultures

DSTs

HIV in Haiti

Rwinkwavu Hospital

Internet in Thomonde, Haití

Use low cost satellites for Internet with generators and solar panels

Developing a common system for the world OpenMRS

Toward a Common Infrastructure

DataData

DataData

DataData

DataData

Toward a Common Infrastructure

DataData

DataData

DataData

DataData

DataData

Toward a Common Infrastructure

DataData

DataData

DataData

DataData

DataDataAPIAPI

Toward a Common Infrastructure

DataData

DataData

DataData

DataData

DataDataDataDataDataDataDataDataAPIAPIAPIAPIAPIAPIAPIAPI

Collaborators and Funders Partners In HealthRegenstrief instituteMedical Research Council, South AfricaWorld Health OrganizationUS Centers for Disease ControlBrigham and Women hospitalHarvard Medical SchoolUniversity of KwaZulu-NatalMillennium Villages ProjectInternational Development Research Centre, OttawaRockefeller FoundationFogarty International Center, NIHBoston Consulting GroupGoogle Inc

Plataform to simplify the creation of clinical systemsCustomizable to local needs

Modular and expandibleUses concept dictionary for data storage

Released with open source license (April 2007)

Uses international standards (HL7, LOINC, SNOMED)

Web-based, but has asynchronous (offline) application

Created by community of developers

OpenMRS

OpenMRS Structure

OpenMRS sites Fall 2008Over 20 countries

USARwanda (PIH)Lesotho (PIH)Peru (PIH)KenyaSouth AfricaTanzaniaUgandaHaitiZimbabwePakistanNorway

Google Maps Integration

Credit: Owais Ahmed, Aamir Khan

Integration of Integration of OpenMRSOpenMRS with with ETR.NetETR.Net and DHISand DHIS

Credit: Chris Seebregts (MRC)

“Mateme” Touchscreen Registration

Credit: Jeff Rafter (Baobab), Evan Waters (PIH)

iPhone App

Credit: Rowan Seymour

African Implementers Network

Commercial Strategies in Latin America

Creating a network of implementers in Latin America

Both NGOs and companies to provide servicesNicaragua, Peru, Bolivia, Chile

Latin American Open Source Health Informatics Meeting

Oct. 26-31Lima, Peru

AcknowledgementsPartners In Health & EMR team, Hamish Fraser,

Socios en Salud, Rapid Methods team, OpenMRS collaborators

www.openMRS.org